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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Marko Matko Ficko Tomaž Kosar Timotej Pliberšek Dijana Močnik Irena Lovrenčič Držanič Ines Kožuh Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Faculty of Electrical Engineering and Computer Science Faculty of Economics and Business University of Maribor Maribor Slovenia Faculty of Social Sciences University of Ljubljana Ljubljana Slovenia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This paper presents the planning and development of the GreenTouch digital tool, a web-based solution designed to improve mental health. The objective of this study was to identify the most suitable technologies for developing a scalable and user-friendly web application by reviewing seven mental health-focused platforms, analyzing their functionalities, and gaining insights into the tools and features they use for mental well-being. The methodology includes a systematic review of functionalities and technologies used in these applications. The analysis led to the identification of key technologies, which were then used to design two potential technology stacks for our solution. The results provide insights into the analysis of app features and the selection of technologies that ensure that both functional and aesthetic requirements are met, offering a strong foundation for the development of the desired web application. This research demonstrates the importance of balancing technical considerations with user experience factors when developing web-based mental health solutions.

关键词： Industries Scalability Mental health User experience Software Planning Mobile applications Time factors Object recognition Systematic literature review

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Automated Deep Learning Pipeline for Accurate Segmentation of Aortic Lumen and Branches in Abdominal Aortic Aneurysm: A Two-Step Approach 2

Automated Deep Learning Pipeline for Accurate Segmentation o...

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2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Hassan, Fatma N. Mahmoud, Ahmed M. Elnokrashy, Ahmed F. Hassan, Ashraf Y. Benha University Benha Faculty of Engineering Department of Electrical Engineering Benha Egypt Cairo University Department of Biomedical Engineering and Systems Giza Egypt Astute Imaging KirklandWA98033 United States Nile University Department of Computer Science Technology and Computer Science Giza Egypt Benha University Benha Egypt

ISBN: (纸本)9798350362633

Abdominal Aortic Aneurysm (AAA) is a serious medical condition characterized by the abnormal enlargement of the abdominal aorta. If left untreated, AAA can have life-threatening consequences. Accurate segmentation of the aorta in Computed Tomography Angiography (CTA) images plays a vital role in treatment planning for AAA. However, manual and semi-automatic segmentation methods suffer from limitations in terms of time and accuracy. This study presents a deep learning pipeline that aims to fully automate the precise and efficient segmentation of the aorta and its branches within CTA images. A two-step approach is proposed for the segmentation of the aorta and its branches in contrast-enhanced CTA scans. The first step involves utilizing a UNet++ model to perform aortic segmentation across the entire set of CTA axial slices. In the second step, a post processing algorithm is employed to track the continuity of the segmented aorta while effectively discarding false positive (FP) objects. The assessment of the fully automated method revealed remarkable outcomes, with a mean Dice coefficient of 0.941 on a test set consisting of 10 CTA scans. The automated segmentation results are utilized to create a comprehensive 3D model. The study results indicate that the utilization of the proposed deep learning-based pipeline is highly effective in achieving accurate segmentation of the aortic lumen and its branches. The practical implications of this approach extend to pre-operative planning. This highlights the valuable contribution of the proposed method in improving the management and treatment of patients diagnosed with aortic aneurysm. © 2024 IEEE.

关键词： computerized tomography

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Enhancing Energy Efficiency in WSNs with Hybrid LEACH-D and ANN

Enhancing Energy Efficiency in WSNs with Hybrid LEACH-D and ...

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2024 Multimedia University engineering Conference, MECON 2024

作者： Qamar, Muhammad Salman Haq, Ihsan Ul Munir, Muhammad Fahad Roslee, Mardeni Bin Awan, Adnan Anwar Waseem, Athar International Islamic University Department of Electrical and Computer Engineering Islamabad Pakistan Multimedia University Centre for Wireless Technology Faculty of Engineering Cyberjaya63100 Malaysia School of Engineering California Polytechnic State University Department of Computer Science and Software Engineering San Luis ObispoCA United States

ISBN: (纸本)9798331530747

This paper explores strategies to improve the energy efficiency and operational longevity of Wireless Sensor Networks (WSNs) through the optimization of clustering techniques and energy efficient routing protocols. The proposed methodology is precisely crafted to optimize energy consumption (EC) while preserving the overall effectiveness of WSNs. LEACH (Low Energy Adaptive Cluster Hierarchy) is a cluster-based protocol where non-cluster head nodes deactivate their RF until their allocated time slots. Nevertheless, a drawback of traditional LEACH is its random rotation of local Cluster Heads (CH), leading to unequal cluster distribution. To overcome this issue, we proposed a novel hybrid technique called LEACH-D protocol and Artificial Neural Network (ANN). The LEACH-D algorithm enhances the duration of transmission tasks while ensuring uniform battery energy consumption. On the other hand, the ANN plays a pivotal role in coordinating optimal routing decisions and CH placement, refining data aggregation and transmission mechanisms to restrain idle listening. The findings indicate that the suggested approach manifests as substantial reductions in energy consumption and prolonged network lifespan of WSN. © 2024 IEEE.

关键词： Sensor nodes

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Quantum Theory Approach to Performance Enhancement in Machine Learning

Quantum Theory Approach to Performance Enhancement in Machin...

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2023 International Conference on science, engineering and Business for Sustainable Development Goals, SEB-SDG 2023

作者： Adebiyi, Marion O. Fatinikun-Olaniyan, Deborah Osang, Francis Adebiyi, Abayomi A. Landmark University Department of Computer Science Nigeria National Open University of Nigeria Department of Computer Science Abuja Nigeria Durban University of Technology Faculty of Engineering and the Built Environment Department Electrical Power Engineering Durban South Africa

ISBN: (纸本)9798350324785

Quantum support vector machines (QSVMs) are a novel approach for solving classification problems, combining the principles of quantum computing with the support vector machine algorithm. In this study, we applied a QSVM to the Breast Cancer Wisconsin (Original) data set to classify tumors as benign or malignant. Our results showed that the QSVM outperformed classical support vector machines in terms of classification accuracy, achieving a success rate of 100% while classical SVM shows almost perfect result with its accuracy 95%. Additionally, the QSVM required significantly less training time compared to the classical SVM. These results demonstrate the potential of QSVMs for solving complex classification problems in the field of medical diagnosis. © 2023 IEEE.

关键词： Classification (of information)

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Optimistic Entanglement Purification in Quantum Networks 4

Optimistic Entanglement Purification in Quantum Networks

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4th IEEE International Conference on Quantum Computing and engineering, QCE 2023

作者： Mobayenjarihani, Mohammad Vardoyan, Gayane Towsley, Don Manning College of Information and Computer Sciences University of Massachusetts Amherst United States Delft University of Technology QuTech Faculty of Electrical Engineering Mathematics and Computer Science United States

ISBN: (纸本)9798350343236

Noise and photon loss encountered on quantum channels pose a major challenge for reliable entanglement generation in quantum networks. In near-term networks, heralding is required to inform endpoints of successfully generated entanglement. If after heralding, entanglement fidelity is too low, entanglement purification may be utilized to probabilistically increase fidelity. Traditionally, purification protocols proceed as follows: generate heralded EPR pairs, execute a series of quantum operations on two or more pairs between two nodes, and classically communicate results to check for success. Purification may require several rounds while qubits are stored in memories, vulnerable to decoherence. In this work, we explore notions of optimistic purification, wherein classical communication required for heralding and purification is delayed, possibly to the end of the process. Optimism reduces the overall time EPR pairs are stored in memory, increasing fidelity while possibly decreasing EPR pair rate due to decreased heralding and purification failure. We apply optimism to the entanglement pumping scheme, ground- and satellite-based EPR generation sources, and current state-of-the-art purification circuits that include several measurement and purification checkpoints. We evaluate performance in view of a number of parameters, including link length, EPR source rate and fidelity;and memory coherence time. We show that while our optimistic protocol increases fidelity, the traditional approach may even decrease fidelity for longer distances. We study the trade-off between rate and fidelity under entanglement-based QKD, and find that optimistic schemes can yield higher rates compared to non-optimistic counterparts, with most advantages seen in scenarios with low initial fidelity and short coherence times. © 2023 IEEE.

关键词： Purification

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Hybrid UHF Quad Antenna for Indoor Use

Hybrid UHF Quad Antenna for Indoor Use

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International Conference on Smart Systems and Technologies (SST)

作者： Tomislav Barić Hrvoje Glavaš Vanja Mandrić Department of Electromechanical Engineering Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Power Engineering Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Communication Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

Amateur ultra-high frequency (UHF) directional antennas intended for indoor use are typically used in confined spaces. Also, their position and orientation often have to be changed, therefore they are exposed to frequent mechanical stress. For this reason, it is preferable that this type of antenna is lightweight, compact, with a mechanically reinforced (strong) construction. Also, it is desirable that the antenna has the best possible electrical and electromagnetic characteristics. This paper presents one of the ways in which the mechanical, electrical and electromagnetic requirements for amateur radio UHF directional indoor antenna can be simultaneously met. In the article, a relatively simple construction of the antenna is proposed. The antenna consists of two vertically stacked hybrid antennas from the Quad antenna family. The paper also presents an interesting choice of materials which ensures a mechanically reinforced (strong) construction and lightweight of the antenna. Numerical calculations and optimizations were carried out using 4nec2 software. Bandwidth and voltage standing wave ratio were determined by measurement.

关键词： Antenna measurements Coaxial cables Voltage measurement Aluminum UHF antennas Soldering Electromagnetics Junctions Antennas Stress

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The GreenTouch Digital Tool Web Development Planning: Comparative Analysis of Mental Health-Focused Web Solutions 24

The GreenTouch Digital Tool Web Development Planning: Compar...

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24th International Symposium INFOTEH-JAHORINA, INFOTEH 2025

作者： Ficko, Marko Matko Kosar, Tomaž Pliberšek, Timotej Močnik, Dijana Držanič, Irena Lovrenčič Kožuh, Ines University of Maribor Faculty of Electrical Engineering and Computer Science Faculty of Economics and Business Maribor Slovenia University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia University of Ljubljana Faculty of Social Sciences Ljubljana Slovenia

ISBN: (纸本)9798331515799

关键词： Web Design

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Energy Theft Identification Using Adaboost Ensembler in the Smart Grids

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computers, Materials & Continua 2022年第7期72卷 2141-2158页

作者： Muhammad Irfan Nasir Ayub Faisal Althobiani Zain Ali Muhammad Idrees Saeed Ullah Saifur Rahman Abdullah Saeed Alwadie Saleh Mohammed Ghonaim Hesham Abdushkour Fahad Salem Alkahtani Samar Alqhtani Piotr Gas Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science Federal Urdu University of Science and TechnologyIslamabad44000Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Computer Science and Engineering University of Engineering and TechnologyNarowal CampusLahore54000Pakistan College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia Department of Electrical and Power Engineering AGH University of Science and Technology Mickiewicza 30 AvenueKrakow30-059Poland

One of the major concerns for the utilities in the Smart Grid(SG)is electricity *** the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously *** this purpose,we have taken historical data of energy thieves and normal *** avoid imbalance observation,biased estimates,we applied the interpolation ***,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further *** proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time *** minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark *** proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,***,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.

关键词： Smart grids and meters electricity theft detection machine learning AdaBoost optimization techniques

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Content Analysis of Medical and Health Apps' rivacy Policies

Frontiers in Artificial Intelligence and Applications

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Frontiers in Artificial Intelligence and Applications 2021年 343卷 188-203页

作者： Brumen, Boštjan Faculty of Electrical Engineering and Computer Science Smetanova 17 MariborSi-2000 Slovenia

ISBN: (纸本)9781643682426

Privacy is a fundamental human right and is widely end extensively protected in the western industrialized world. The recent advances in technologies, especially in the use of applications developed and designed for mobile devices, have led to the rise of its abuse on one hand and a higher awareness of the importance of privacy on the other side. Legal texts protecting privacy have attempted to rectify some of the problems, but the ecosystem giants and mobile apps developers adapted. In this paper, we analyze which data mobile apps developers are collecting. We have focused on a sample of apps in the medical and health field. The research was done using collocations analysis. A relationship between a base word and its collocative partners was sought. The initial visual results have led us to more detailed studies that unveiled some worrying patterns. Namely, applications are collect data about the users and their activities, but also about their family members, medical diagnoses, treatments, and alike, going well beyond the 'need to function' / functionality threshold. © 2021 The authors and IOS Press.

关键词： mHealth

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Parallel Binary QUasi-Affine TRansformation Evolution (QUATRE) Algorithm 1

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18th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Zhuang, Zhongjie Chu, Shu-Chuan Pan, Jeng-Shyang Snašel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China College of Science and Engineering Flinders University 1284 South Road Clovelly ParkSA5042 Australia Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava Czech Republic

ISBN: (数字)9789819906055

ISBN: (纸本)9789819906048

QUasi-Affine TRansformation Evolutionary (QUATRE) generalized differential evolution algorithm to matrix form, which was designed for solving continuous problems. Binary QUATRE (BQUATRE) algorithm convert the original BQUATRE to the binary form to deal with hyperspectral dimensionality reduction. In this paper, in order to further improve the performance of the BQUATRE, the parallel mechanism is introduced to BQUATRE, and proposed parallel binary BQUATRE algorithm (PBQUATRE). The global best solution and the group best solution both guide the position update of other solutions with a probability of 0.5 in communication phase. The mutation matrix B is also affected not only by the global best solution but also by the group best solution. The proposed algorithm is applied for feature selection and hyperspectral dimensionality reduction, and experimental results show that the proposed PBQUATRE is superior to the classics and state-of-the-art algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Linear transformations

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